Update app.py

app.py

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+from typing import TextIO
+import keras_cv
+from translate import Translator
+import matplotlib.pyplot as plt
+import gradio as gr
+import tensorflow as tf
+
+model = keras_cv.models.StableDiffusion(img_width=512, img_height=512)
+translator = Translator(from_lang="ko", to_lang="en")
+
+
+def generate_img(text:str, cnt:int) -> list:
+    #입력 받은 텍스트를 cnt개의 이미지로 생성하여 return
+
+    text = translator.translate(text)
+    images = model.text_to_image(text, batch_size=cnt)
+    return images
+
+def plot_image(images) -> None:
+    #입력 받은 이미지들을 이미지로 저장
+    plt.figure(figsize=(20, 20))
+
+    for i in range(len(images)):
+        ax = plt.subplot(1, len(images), i + 1)
+        plt.imshow(images[i])
+        plt.axis("off")
+        plt.tight_layout()
+
+
+    plt.savefig(f"text.png")
+
+
+def inference(text:str):
+    image = generate_img(text, 1).squeeze()
+    return image
+
+with gr.Blocks(theme=gr.themes.Base()) as demo:
+
+  with gr.Row():
+    with gr.Column():
+      
+      text=gr.Textbox(lines=5,placeholder='Prompt here',label="prompt")
+      create_btn = gr.Button(value="Create")
+    with gr.Column():
+      output=gr.Image(shape=(200,200))
+  create_btn.click(fn=inference,inputs=text,outputs=output)
+  examples = gr.Examples(examples=["The rainbow car", "Ride the cloud into the night sky"],inputs=[text])
+    
+
+demo.launch(share=False)